Browsing by Subject "Electroencephalography"

Now showing 1 - 2 of 2
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    Decoding load or selection in visuospatial working memory?
    (Wiley, 2024-10) Tortajada, Miriam; Fahrenfort, Johannes J.; Sandoval Lentisco, Alejandro; Palmero, Lucía B.; Castillo, Alejandro; Fuentes Melero, Luis José; Campoy, Guillermo; Olivers, Christian N. L.; Martínez Pérez, Víctor; Psicología Básica y Metodología
    Flexible updating of information in Visual Working Memory (VWM) is crucial to deal with its limited capacity. Previous research has shown that the removal of no longer relevant information takes some time to complete. Here, we sought to study the time course of such removal by tracking the accompanying drop in load through behavioral and neurophysiological measures. In the first experimental session, participants completed a visuospatial retro-cue task in which the Cue-Target Interval (CTI) was manipulated. The performance revealed that it takes about half a second to make full use of the retro-cue. In a second session, we sought to study the dynamics of load-related electroencephalographic (EEG) signals to track the removal of information. We applied Multivariate Pattern Analysis (MVPA) to EEG data from the same task. Right after encoding, results replicated previous research using MVPA to decode load. However, especially after the retro-cue, results suggested that classifiers were mainly sensitive to a selection component, and not so much to load per se. Additionally, visual cue variations, as well as eye movements that accompany load manipulations can also contribute to decoding. These findings advise caution when using MVPA to decode VWM load, as classifiers may be sensitive to confounding operations.
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    Sleep EEG derived from behind-the-ear electrodes (cEEGrid) compared to standard polysomnography: a proof of concept study
    (Frontiers Media, 2018-11-26) Sterr, Annette; Ebajemito, James K.; Mikkelsen, Kaare B.; Santhi, Nayantara; Monica, Ciro della; Grainger, Lucinda; Atzori, Giuseppe; Revell, Victoria L.; Debener, Stefan; Dijk, Derk-Jan; DeVos, Maarten; Bonmatí Carrión, María de los Ángeles; Anatomía Humana y Psicobiología
    Electroencephalography (EEG) recordings represent a vital component of the assessment of sleep physiology, but the methodology presently used is costly, intrusive to participants, and laborious in application. There is a recognized need to develop more easily applicable yet reliable EEG systems that allow unobtrusive long-term recording of sleep-wake EEG ideally away from the laboratory setting. cEEGrid is a recently developed flex-printed around-the-ear electrode array, which holds great potential for sleep-wake monitoring research. It is comfortable to wear, simple to apply, and minimally intrusive during sleep. Moreover, it can be combined with a smartphone-controlled miniaturized amplifier and is fully portable. Evaluation of cEEGrid as a motion-tolerant device is ongoing, but initial findings clearly indicate that it is very well suited for cognitive research. The present study aimed to explore the suitability of cEEGrid for sleep research, by testing whether cEEGrid data affords the signal quality and characteristics necessary for sleep stage scoring. In an accredited sleep laboratory, sleep data from cEEGrid and a standard PSG system were acquired simultaneously. Twenty participants were recorded for one extended nocturnal sleep opportunity. Fifteen data sets were scored manually. Sleep parameters relating to sleep maintenance and sleep architecture were then extracted and statistically assessed for signal quality and concordance. The findings suggest that the cEEGrid system is a viable and robust recording tool to capture sleep and wake EEG. Further research is needed to fully determine the suitability of cEEGrid for basic and applied research as well as sleep medicine.